val visits = Seq(
(0, "Warsaw", 2015),
(1, "Warsaw", 2016),
(2, "Boston", 2017)
).toDF("id", "city", "year")
val q = visits
.groupBy("city")
.pivot("year", Seq("2015", "2016", "2017"))
.count()
scala> println(q.queryExecution.logical.numberedTreeString)
00 Pivot [city#8], year#9: int, [2015, 2016, 2017], [count(1) AS count#157L]
01 +- Project [_1#3 AS id#7, _2#4 AS city#8, _3#5 AS year#9]
02 +- LocalRelation [_1#3, _2#4, _3#5]
Pivot Unary Logical Operator
Pivot
is a unary logical operator that represents pivot operator.
Pivot
is created when RelationalGroupedDataset
creates a DataFrame for an aggregate operator.
Analysis Phase
Pivot
operator is resolved at analysis phase in the following logical evaluation rules:
val spark: SparkSession = ...
import spark.sessionState.analyzer.ResolveAliases
// see q in the example above
val plan = q.queryExecution.logical
scala> println(plan.numberedTreeString)
00 Pivot [city#8], year#9: int, [2015, 2016, 2017], [count(1) AS count#24L]
01 +- Project [_1#3 AS id#7, _2#4 AS city#8, _3#5 AS year#9]
02 +- LocalRelation [_1#3, _2#4, _3#5]
// FIXME Find a plan to show the effect of ResolveAliases
val planResolved = ResolveAliases(plan)
Pivot
operator "disappears" behind (i.e. is converted to) a Aggregate logical operator (possibly under Project
operator).
import spark.sessionState.analyzer.ResolvePivot
val planAfterResolvePivot = ResolvePivot(plan)
scala> println(planAfterResolvePivot.numberedTreeString)
00 Project [city#8, __pivot_count(1) AS `count` AS `count(1) AS ``count```#62[0] AS 2015#63L, __pivot_count(1) AS `count` AS `count(1) AS ``count```#62[1] AS 2016#64L, __pivot_count(1) AS `count` AS `count(1) AS ``count```#62[2] AS 2017#65L]
01 +- Aggregate [city#8], [city#8, pivotfirst(year#9, count(1) AS `count`#54L, 2015, 2016, 2017, 0, 0) AS __pivot_count(1) AS `count` AS `count(1) AS ``count```#62]
02 +- Aggregate [city#8, year#9], [city#8, year#9, count(1) AS count#24L AS count(1) AS `count`#54L]
03 +- Project [_1#3 AS id#7, _2#4 AS city#8, _3#5 AS year#9]
04 +- LocalRelation [_1#3, _2#4, _3#5]
Creating Pivot Instance
Pivot
takes the following when created:
-
Grouping named expressions
-
Pivot column expression
-
Pivot values literals
-
Aggregation expressions
-
Child logical plan